"No one can promise that this will work, at least it will work by itself!"

About the Lazy Trading Courses:
This series of courses is designed totocombine fascinating experience ofAlgorithmic Trading and at the same time tolearn Computer andData Science! Particular focus is made on buildingDecision Support System that can help to automate a lot of boring processes related to Trading and also learn Data Science. Several algorithms will be built by performing basic data cycle 'data input-data manipulation - analysis -output'. Provided examples throughout all 7 courses will show how to build very comprehensive system capable to automatically evolve without much manual input.

About this Course:Developing Self Learning Trading Robot with Statistical Modeling

This course will cover usage of Deep Learning Regression Model to predict future prices of financial asset. This course will blend everything that was previously explained to use:

• Use MQL4 DataWriter robot to gather financial asset data

• UseR Statistical Software to aggregate data to be ready for modeling

• Use H2O Machine Learning Platform to train Deep Learning Regression Models

  • Use random neural network structures

  • Functions with test and examples in R package

• Back-test trading strategy using Model prediction and historical data

• ... update model if needed

• Use Model and New Datato generate predictions

• Use Model output in MQL4Trading Robot

• Adding and using Market Type info [from course 6]

• Experiment by adding Reinforcement Learning to select best possible Market Type

"What is that ONEthing very special about this course?"

-- Watch AI predicting the future!

This project iscontaining several coursesfocused to help managing Automated Trading Systems:

1. Set up your Home Trading Environment

2. Set up your Trading Strategy Robot

3. Set up your automatedTrading Journal

4. Statistical Automated Trading Control

5. Reading News and Sentiment Analysis

6. Using Artificial Intelligence to detect market status

7. Building anAI trading system

IMPORTANT:all courses will have a 'quick to deploy' sections as well as sections containing theoretical explanations.

What will you learn apart of trading:

While completing thesecourses you will learn much more rather than just trading by using provided examples:

• Learn and practice to use Decision Support System

• Be organized and systematic using Version Control and Automated Statistical Analysis

• Learn using R to read, manipulate data and perform Machine Learning including Deep Learning

• Learn and practiceData Visualization

• Learn sentiment analysis and web scrapping

• Learn Shiny to deploy any data project in hours

• Get productivity hacks

• Learn to automate your tasksand scheduling them

• Get expandable examples of MQL4 and R code

What these courses are not:

• These courses will not teach and explain specific programming concepts in details

• These courses are not meant to teach basics of Data Science or Trading

• There is no guarantee onbug free programming

Disclaimer:

Trading is a risk. This course must not be intended as a financial advice or service. Past results are not guaranteed for the future. Significant time investment may be required to reproduce proposed methods and concepts